Collecting distributed network data for analysis of learning

I recorded a conversation with Kirsty Kitto and Leo Gaggle, the most knowledgable people I know when it comes to #xapi#LRS and #learninganalytics applied in distributed networks (the Internet, or “the wild” as Kirsty likes to call it).

Kirsty leads a national OLT project to the tune of $320000 over 2 years, developing a toolkit (available on GitHub) for collecting data from the wider internet and beginning to make sense of it for specific learning analysis.

The video is fully logged with hyperlinked timecodes and URLs in the description (and below to aid search in this website). I suggest you set youtube to watch at 2x speed and use the time codes to jump around if you need.

Streamed live on Jul 17, 2016

0:00 Kirsty Kitto at QUT and Leo Gaggle at Bright Cookie http://www.brightcookie.com/ thanks for joining us. We’re meeting to discuss methods for extracting data from a specified Youtube network, and how we might use that data to analyse the network

0:25 Leo explains why we’re meeting. Coming from a conversation about Experience API (XAPI) and how we might use it to gather data from online networks. Leo suggested we talk with Kirsty Kitto who has been working with XAPI to do such things

1:20 Kirsty explains how her team is using XAPI to extract data from social media networks. It is a project funded by the Office of Learning and Teaching (OLT) that has been running for a little over a year.http://users.on.net/~kirsty.kitto/pro… Twitter, WordPress, Trello and GitHub. Works with teachers who don’t use Learning Management Systems, but use various social network services instead.

14:00 drawing in hashtags from Twitter and discussion about student privacy

17:00 Leo Gaggle talking about the developments at Bright Cookie and some of the difficulties with xAPI, but using it to draw in multiple feeds of data for reporting. Using xAPI to report professional development activities in the corporate environments. Basically using xAPI and LRS to recreate an LMS reporting system, but from more distributed feeds of data.

20:40 Describing the RMIT project to create a learning network in Youtube, where a teacher creates a channel (in this case, “Andrew Robinson Footwear”) and the students create accounts and subscribe to that channel, and each other. The teacher subscribes to the School channels and other teachers. One of our questions is, can we teach youtube to teach? http://dsctal.space/2016/06/17/teaching… Can we establish a connected online proffessional network inside Youtube that can go with a student when they graduate? What sort of data can we extract from that network?

25:10 Kirsty recognises the value of the project. But there are problems with Youtube’s API and the quality of the data, such as view stats. To assess networks, we need all parties subscribed to the toolkit. (After the recording, Leo suggested dropping Google Analytics in on each channel of the network).

30:10 Leo explains how to capture play events in an iFrame embeded into a web page with a player app. Discussion about student participation, and connecting qualitative data gathering.

34:25 Kirsty talks about capturing Youtube comments, as well as “mini LMS” that captures all user’s click streams. Also suggested tracking memes, with a competition between students – who can send their video the furthest, and how do we track that.

38:38 Leo makes the point that xAPI only helps with the collection of data. The big work is in analysis.

40:00 RMIT is aiming to host a datahack to try and solve analytical challenges. Solid advice on the need to get the data structures thought through before the data hack. Leo points to the recipes that Kirsty’s team has created could be a good starting point. https://github.com/kirstykitto

43:00 Kirsty’s solid advice to watch the wider scene of systems like xAPI to try and ensure the interoperability of data for long term use.

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